function t_mips6(quiet)
%------------------------------  deprecated  ------------------------------
%   MATLAB 6.x support to be removed in a future version.
%--------------------------------------------------------------------------
%T_MIPS6  Tests of MIPS NLP solver (for MATLAB 6).

%   MIPS
%   $Id: t_mips6.m 4738 2014-07-03 00:55:39Z dchassin $
%   by Ray Zimmerman, PSERC Cornell
%   Copyright (c) 2010 by Power System Engineering Research Center (PSERC)
%
%   This file is part of MIPS.
%   See http://www.pserc.cornell.edu/matpower/ for more info.
%
%   MIPS is free software: you can redistribute it and/or modify
%   it under the terms of the GNU General Public License as published
%   by the Free Software Foundation, either version 3 of the License,
%   or (at your option) any later version.
%
%   MIPS is distributed in the hope that it will be useful,
%   but WITHOUT ANY WARRANTY; without even the implied warranty of
%   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
%   GNU General Public License for more details.
%
%   You should have received a copy of the GNU General Public License
%   along with MIPS. If not, see <http://www.gnu.org/licenses/>.
%
%   Additional permission under GNU GPL version 3 section 7
%
%   If you modify MIPS, or any covered work, to interface with
%   other modules (such as MATLAB code and MEX-files) available in a
%   MATLAB(R) or comparable environment containing parts covered
%   under other licensing terms, the licensors of MIPS grant
%   you additional permission to convey the resulting work.

if nargin < 1
    quiet = 0;
end

t_begin(60, quiet);

t = 'unconstrained banana function : ';
%% from MATLAB Optimization Toolbox's bandem.m
f_fcn = @f2;
x0 = [-1.9; 2];
% [x, f, s, out, lam] = mips6(f_fcn, x0, [], [], [], [], [], [], [], struct('verbose', 2));
[x, f, s, out, lam] = mips6(f_fcn, x0);
t_is(s, 1, 13, [t 'success']);
t_is(x, [1; 1], 13, [t 'x']);
t_is(f, 0, 13, [t 'f']);
t_is(out.hist(end).compcond, 0, 6, [t 'compcond']);
t_ok(isempty(lam.mu_l), [t 'lam.mu_l']);
t_ok(isempty(lam.mu_u), [t 'lam.mu_u']);
t_is(lam.lower, zeros(size(x)), 13, [t 'lam.lower']);
t_is(lam.upper, zeros(size(x)), 13, [t 'lam.upper']);

t = 'unconstrained 3-d quadratic : ';
%% from http://www.akiti.ca/QuadProgEx0Constr.html
f_fcn = @f3;
x0 = [0; 0; 0];
% [x, f, s, out, lam] = mips6(f_fcn, x0, [], [], [], [], [], [], [], struct('verbose', 2));
[x, f, s, out, lam] = mips6(f_fcn, x0);
t_is(s, 1, 13, [t 'success']);
t_is(x, [3; 5; 7], 13, [t 'x']);
t_is(f, -244, 13, [t 'f']);
t_is(out.hist(end).compcond, 0, 6, [t 'compcond']);
t_ok(isempty(lam.mu_l), [t 'lam.mu_l']);
t_ok(isempty(lam.mu_u), [t 'lam.mu_u']);
t_is(lam.lower, zeros(size(x)), 13, [t 'lam.lower']);
t_is(lam.upper, zeros(size(x)), 13, [t 'lam.upper']);

t = 'constrained 4-d QP : ';
%% from http://www.jmu.edu/docs/sasdoc/sashtml/iml/chap8/sect12.htm
f_fcn = @f4;
x0 = [1; 0; 0; 1];
A = [   1       1       1       1;
        0.17    0.11    0.10    0.18    ];
l = [1; 0.10];
u = [1; Inf];
xmin = zeros(4,1);
% [x, f, s, out, lam] = mips6(f_fcn, x0, A, l, u, xmin, [], [], [], struct('verbose', 2));
[x, f, s, out, lam] = mips6(f_fcn, x0, A, l, u, xmin);
t_is(s, 1, 13, [t 'success']);
t_is(x, [0; 2.8; 0.2; 0]/3, 6, [t 'x']);
t_is(f, 3.29/3, 6, [t 'f']);
t_is(out.hist(end).compcond, 0, 6, [t 'compcond']);
t_is(lam.mu_l, [6.58;0]/3, 6, [t 'lam.mu_l']);
t_is(lam.mu_u, [0;0], 13, [t 'lam.mu_u']);
t_is(lam.lower, [2.24;0;0;1.7667], 4, [t 'lam.lower']);
t_is(lam.upper, zeros(size(x)), 13, [t 'lam.upper']);

H = [   1003.1  4.3     6.3     5.9;
        4.3     2.2     2.1     3.9;
        6.3     2.1     3.5     4.8;
        5.9     3.9     4.8     10  ];
c = zeros(4,1);
% %% check with quadprog (for dev testing only)
% [x, f, s, out, lam] = quadprog(H,c,-A(2,:), -0.10, A(1,:), 1, xmin);
% t_is(s, 1, 13, [t 'success']);
% t_is(x, [0; 2.8; 0.2; 0]/3, 6, [t 'x']);
% t_is(f, 3.29/3, 6, [t 'f']);
% t_is(lam.eqlin, -6.58/3, 6, [t 'lam.eqlin']);
% t_is(lam.ineqlin, 0, 13, [t 'lam.ineqlin']);
% t_is(lam.lower, [2.24;0;0;1.7667], 4, [t 'lam.lower']);
% t_is(lam.upper, [0;0;0;0], 13, [t 'lam.upper']);

t = 'constrained 2-d nonlinear : ';
%% from http://en.wikipedia.org/wiki/Nonlinear_programming#2-dimensional_example
f_fcn = @f5;
gh_fcn = @gh5;
hess_fcn = @hess5;
x0 = [1.1; 0];
xmin = zeros(2, 1);
% xmax = 3 * ones(2, 1);
% [x, f, s, out, lam] = mips6(f_fcn, x0, [], [], [], xmin, [], gh_fcn, hess_fcn, struct('verbose', 2));
[x, f, s, out, lam] = mips6(f_fcn, x0, [], [], [], xmin, [], gh_fcn, hess_fcn);
t_is(s, 1, 13, [t 'success']);
t_is(x, [1; 1], 6, [t 'x']);
t_is(f, -2, 6, [t 'f']);
t_is(out.hist(end).compcond, 0, 6, [t 'compcond']);
t_is(lam.ineqnonlin, [0;0.5], 6, [t 'lam.ineqnonlin']);
t_ok(isempty(lam.mu_l), [t 'lam.mu_l']);
t_ok(isempty(lam.mu_u), [t 'lam.mu_u']);
t_is(lam.lower, zeros(size(x)), 13, [t 'lam.lower']);
t_is(lam.upper, zeros(size(x)), 13, [t 'lam.upper']);
% %% check with fmincon (for dev testing only)
% % fmoptions = optimset('Algorithm', 'interior-point');
% % [x, f, s, out, lam] = fmincon(f_fcn, x0, [], [], [], [], xmin, [], gh_fcn, fmoptions);
% [x, f, s, out, lam] = fmincon(f_fcn, x0, [], [], [], [], [], [], gh_fcn);
% t_is(s, 1, 13, [t 'success']);
% t_is(x, [1; 1], 4, [t 'x']);
% t_is(f, -2, 6, [t 'f']);
% t_is(lam.ineqnonlin, [0;0.5], 6, [t 'lam.ineqnonlin']);

t = 'constrained 3-d nonlinear : ';
%% from http://en.wikipedia.org/wiki/Nonlinear_programming#3-dimensional_example
f_fcn = @f6;
gh_fcn = @gh6;
hess_fcn = @hess6;
x0 = [1; 1; 0];
% [x, f, s, out, lam] = mips6(f_fcn, x0, [], [], [], [], [], gh_fcn, hess_fcn, struct('verbose', 2, 'comptol', 1e-9));
[x, f, s, out, lam] = mips6(f_fcn, x0, [], [], [], [], [], gh_fcn, hess_fcn);
t_is(s, 1, 13, [t 'success']);
t_is(x, [1.58113883; 2.23606798; 1.58113883], 6, [t 'x']);
t_is(f, -5*sqrt(2), 6, [t 'f']);
t_is(out.hist(end).compcond, 0, 6, [t 'compcond']);
t_is(lam.ineqnonlin, [0;sqrt(2)/2], 7, [t 'lam.ineqnonlin']);
t_ok(isempty(lam.mu_l), [t 'lam.mu_l']);
t_ok(isempty(lam.mu_u), [t 'lam.mu_u']);
t_is(lam.lower, zeros(size(x)), 13, [t 'lam.lower']);
t_is(lam.upper, zeros(size(x)), 13, [t 'lam.upper']);
% %% check with fmincon (for dev testing only)
% % fmoptions = optimset('Algorithm', 'interior-point');
% % [x, f, s, out, lam] = fmincon(f_fcn, x0, [], [], [], [], xmin, [], gh_fcn, fmoptions);
% [x, f, s, out, lam] = fmincon(f_fcn, x0, [], [], [], [], [], [], gh_fcn);
% t_is(s, 1, 13, [t 'success']);
% t_is(x, [1.58113883; 2.23606798; 1.58113883], 4, [t 'x']);
% t_is(f, -5*sqrt(2), 8, [t 'f']);
% t_is(lam.ineqnonlin, [0;sqrt(2)/2], 8, [t 'lam.ineqnonlin']);

t = 'constrained 3-d nonlinear (struct) : ';
p = struct('f_fcn', f_fcn, 'x0', x0, 'gh_fcn', gh_fcn, 'hess_fcn', hess_fcn);
[x, f, s, out, lam] = mips6(p);
t_is(s, 1, 13, [t 'success']);
t_is(x, [1.58113883; 2.23606798; 1.58113883], 6, [t 'x']);
t_is(f, -5*sqrt(2), 6, [t 'f']);
t_is(out.hist(end).compcond, 0, 6, [t 'compcond']);
t_is(lam.ineqnonlin, [0;sqrt(2)/2], 7, [t 'lam.ineqnonlin']);
t_ok(isempty(lam.mu_l), [t 'lam.mu_l']);
t_ok(isempty(lam.mu_u), [t 'lam.mu_u']);
t_is(lam.lower, zeros(size(x)), 13, [t 'lam.lower']);
t_is(lam.upper, zeros(size(x)), 13, [t 'lam.upper']);

t = 'constrained 4-d nonlinear : ';
%% Hock & Schittkowski test problem #71
f_fcn = @f7;
gh_fcn = @gh7;
hess_fcn = @hess7;
x0 = [1; 5; 5; 1];
xmin = ones(4, 1);
xmax = 5 * xmin;
% [x, f, s, out, lam] = mips6(f_fcn, x0, [], [], [], xmin, xmax, gh_fcn, hess_fcn, struct('verbose', 2, 'comptol', 1e-9));
[x, f, s, out, lam] = mips6(f_fcn, x0, [], [], [], xmin, xmax, gh_fcn, hess_fcn);
t_is(s, 1, 13, [t 'success']);
t_is(x, [1; 4.7429994; 3.8211503; 1.3794082], 6, [t 'x']);
t_is(f, 17.0140173, 6, [t 'f']);
t_is(lam.eqnonlin, 0.1614686, 5, [t 'lam.eqnonlin']);
t_is(lam.ineqnonlin, 0.55229366, 5, [t 'lam.ineqnonlin']);
t_ok(isempty(lam.mu_l), [t 'lam.mu_l']);
t_ok(isempty(lam.mu_u), [t 'lam.mu_u']);
t_is(lam.lower, [1.08787121024; 0; 0; 0], 5, [t 'lam.lower']);
t_is(lam.upper, zeros(size(x)), 7, [t 'lam.upper']);

t_end;


% %%-----  eg99 : linearly constrained fmincon example, mips can't solve  -----
% function [f, df, d2f] = eg99(x)
% f = -x(1)*x(2)*x(3);
% df = -[ x(2)*x(3);
%         x(1)*x(3);
%         x(1)*x(2)   ];
% d2f = -[    0       x(3)    x(2);
%             x(3)    0       x(1);
%             x(2)    x(1)    0   ];
% end
% 
% x0 = [10;10;10];
% A = [1 2 2];
% l = 0;
% u = 72;
% fmoptions = optimset('Display', 'testing');
% fmoptions = optimset(fmoptions, 'Algorithm', 'interior-point');
% [x, f, s, out, lam] = fmincon(f_fcn, x0, [-A; A], [-l; u], [], [], [], [], [], fmoptions);
% t_is(x, [24; 12; 12], 13, t);
% t_is(f, -3456, 13, t);


%% unconstrained banana function
%% from MATLAB Optimization Toolbox's bandem.m
function [f, df, d2f] = f2(x, varargin)
    a = 100;
    f = a*(x(2)-x(1)^2)^2+(1-x(1))^2;
    df = [  4*a*(x(1)^3 - x(1)*x(2)) + 2*x(1)-2;
            2*a*(x(2) - x(1)^2)                     ];
    d2f = 4*a*[ 3*x(1)^2 - x(2) + 1/(2*a),  -x(1);
                -x(1)                       1/2       ];


%% unconstrained 3-d quadratic
%% from http://www.akiti.ca/QuadProgEx0Constr.html
function [f, df, d2f] = f3(x, varargin)
    H = [5 -2 -1; -2 4 3; -1 3 5];
    c = [2; -35; -47];
    f = 1/2 * x'*H*x + c'*x + 5;
    df = H*x + c;
    d2f = H;


%% constrained 4-d QP
%% from http://www.jmu.edu/docs/sasdoc/sashtml/iml/chap8/sect12.htm
function [f, df, d2f] = f4(x, varargin)
    H = [   1003.1  4.3     6.3     5.9;
            4.3     2.2     2.1     3.9;
            6.3     2.1     3.5     4.8;
            5.9     3.9     4.8     10  ];
    c = zeros(4,1);
    f = 1/2 * x'*H*x + c'*x;
    df = H*x + c;
    d2f = H;


%% constrained 2-d nonlinear
%% from http://en.wikipedia.org/wiki/Nonlinear_programming#2-dimensional_example
function [f, df, d2f] = f5(x, varargin)
    c = -[1; 1];
    f = c'*x;
    df = c;
    d2f = zeros(2,2);

function [h, g, dh, dg] = gh5(x, varargin)
    h = [ -1 -1; 1 1] * x.^2 + [1; -2];
    dh = 2 * [-x(1) x(1); -x(2) x(2)];
    g = []; dg = [];

function Lxx = hess5(x, lam, cost_mult, varargin)
    mu = lam.ineqnonlin;
    Lxx = 2*[-1 1]*mu*eye(2);


%% constrained 3-d nonlinear
%% from http://en.wikipedia.org/wiki/Nonlinear_programming#3-dimensional_example
function [f, df, d2f] = f6(x, varargin)
    f = -x(1)*x(2) - x(2)*x(3);
    df = -[x(2); x(1)+x(3); x(2)];
    d2f = -[0 1 0; 1 0 1; 0 1 0];

function [h, g, dh, dg] = gh6(x, varargin)
    h = [ 1 -1 1; 1 1 1] * x.^2 + [-2; -10];
    dh = 2 * [x(1) x(1); -x(2) x(2); x(3) x(3)];
    g = []; dg = [];

function Lxx = hess6(x, lam, cost_mult, varargin)
    if nargin < 3, cost_mult = 1; end
    mu = lam.ineqnonlin;
    Lxx = cost_mult * [0 -1 0; -1 0 -1; 0 -1 0] + ...
            [2*[1 1]*mu 0 0; 0 2*[-1 1]*mu 0; 0 0 2*[1 1]*mu];


%% constrained 4-d nonlinear
%% Hock & Schittkowski test problem #71
function [f, df, d2f] = f7(x, varargin)
    f = x(1)*x(4)*sum(x(1:3)) + x(3);
    df = [ x(1)*x(4) + x(4)*sum(x(1:3));
		   x(1)*x(4);
		   x(1)*x(4) + 1;
		   x(1)*sum(x(1:3)) ];
    d2f = sparse([ 2*x(4)        x(4)   x(4)  2*x(1)+x(2)+x(3);
              x(4)               0      0     x(1);
              x(4)               0      0     x(1);
              2*x(1)+x(2)+x(3)  x(1)  x(1)    0
    	]);

function [h, g, dh, dg] = gh7(x, varargin)
    g = sum(x.^2) - 40;
    h = -prod(x) + 25;
	dg = 2*x;
	dh = -prod(x)./x;

function Lxx = hess7(x, lam, sigma, varargin)
	if nargin < 3, sigma = 1; end
    lambda = lam.eqnonlin;
    mu     = lam.ineqnonlin;
    [f, df, d2f] = f7(x);
    Lxx = sigma * d2f + lambda*2*speye(4) - ...
       mu*sparse([      0     x(3)*x(4) x(2)*x(4) x(2)*x(3);
                    x(3)*x(4)     0     x(1)*x(4) x(1)*x(3);
                    x(2)*x(4) x(1)*x(4)     0     x(1)*x(2);
                    x(2)*x(3) x(1)*x(3) x(1)*x(2)     0  ]);
